Crystal identification may be performed for a single imaging modality system and/or a multi-modality imaging system with a positron emission tomography (PET) detector/scanner, especially for a high-resolution PET device. PET uses a large number of scintillator crystals (or referred to as crystals for brevity) of a small size in its detector blocks. The small size of the crystals may result in low signal-to-noise ratio (SNR); the large number of the crystals may lead to distortion of crystal array during signal encoding/decoding process, making it challenging to identify crystals in a PET detector.
Crystal identification may involve segmentation of a flood histogram into regions equal to the total number of scintillator crystals in the detector array, such that each region has one peak. A peak may correspond to the central position of the distribution of the events detected in one crystal. A region with a peak may correspond to the location and the size of the crystal. Existing segmentation schemes are derived from a broad range of image processing and pattern recognition techniques. A relatively straightforward scheme is to manually click on peak locations on a computer screen and then segment the individual regions, which is labor intensive and time-consuming. Thus, there exists a need in the field to provide a method and system for crystal identification that may address these and other technical challenges.